由於六十秭赫附近存在著廣大的無需執照頻寬，因此六十秭赫頻帶的通訊技術近來受到了許多關注。IEEE 802.15.3c工作團隊制定了中心頻率於六十秭赫之無線個人區域網路的通道模型和相關標準，這裡我們將多輸入多輸出正交分頻多工 (Multiple-Input-Multiple-Output Orthogonal Frequency Division Multiplexing, MIMO-OFDM) 系統應用於IEEE 802.15.3c通道模型下，並且我們考慮有多位使用者正同時在進行通訊，在這種狀況下使用者彼此會互相干擾而影響到通訊品質，干擾對齊技術 (Interference Alignment, IA) 是一種有能有效降低使用者之間干擾影響的方法。
然而，現有的干擾對齊技術之疊代演算法無法保證能收斂到全局極值，在本論文中，我們藉由互換演算法的代價函數來趨近一個效能較佳的區域極值。另外，在多載波的系統下，現有的干擾對齊技術之疊代演算法必須對所有的子載波個別做預編碼矩陣和結合矩陣的設計，我們將演算法改良為對一群子載波做預編碼矩陣和結合矩陣的設計以期降低系統複雜度。最後，我們對現有的和我們所改良後的演算法進行複雜度分析及數值模擬來分析結果。

Owing to the large amount of unlicensed bandwidth in its spectral vicinity, 60 GHz technology has attracted much attention as a means for meeting the growing requirements for high-rate indoor wireless communication. In this thesis, the multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) technique is considered for the IEEE 802.15.3c 60 GHz indoor channel model. In multi-user systems, inter-user interference (IUI) affects the system performance, and interference alignment (IA) is a promising technique for mitigating IUI. Therefore, iterative algorithms of IA are considered in the thesis.
As currently used iterative algorithms of IA are shown to easily fall into local minima, we propose two algorithms for improving the performance by switching cost functions. Another problem with current iterative algorithms is that precoding and combining matrices must be calculated for each subcarrier, which increases the complexity for systems with a large number of subcarriers. We modify two iterative algorithms of IA into carrier grouping type, enabling the system complexity to be reduced through designing precoding and combining matrices for a group of subcarriers. As the initial value is known to be crucial for iterative algorithms, we also introduce a method to choose the initial value for carrier grouping algorithms. Finally, simulation results are shown to compare the performance of each scheme.

1. Introduction 1
2. 60 GHz Indoor Channel and System Models 5
2.1 Overview of 60 GHz Indoor Channel Model . . . . . . . . . . . . . . . . . . 5
2.2 Multi-user MIMO-OFDM System Model . . . . . . . . . . . . . . . . . . . . 9
3. Interference Alignment Algorithms 20
3.1 Iterative Interference Alignment Algorithm . . . . . . . . . . . . . . . . . . . 20
3.2 Maximum SINR Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4. Switched Interference Alignment Algorithms 26
4.1 Switched Interference Alignment Algorithm . . . . . . . . . . . . . . . . . . 26
4.2 Weighted Iterative Interference Alignment Algorithm . . . . . . . . . . . . . 27
4.3 Weighted Switched Interference Alignment Algorithm . . . . . . . . . . . . . 30
4.4 Time Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5. Interference Alignment Algorithms with Carrier Grouping 34
5.1 Iterative Interference Alignment Algorithm with Carrier Grouping . . . . . . 34
5.2 Maximum SINR Algorithm with Carrier Grouping . . . . . . . . . . . . . . . 37
5.3 Time Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
5.4 Initial Value for Interference Alignment Algorithms with Carrier Grouping . 41
6. Simulation Results 44
6.1 Performance Comparison for Switched Interference Alignment Algorithms . . 46
6.2 Performance Comparison for Interference Alignment Algorithms with Carrier
Grouping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3 Effects of Initialization on Interference Alignment Algorithms with Carrier Grouping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7. Conclusion 70

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